Hi!
I am Alessio, a Pre-Doctoral Fellow at Bocconi University :)
I am Alessio, a Pre-Doctoral Fellow at Bocconi University :)
I recently graduated with a M.Sc. in Economics and Econometrics from the University of Bologna, with coursework in Labor, Panel Data, & Dynamic Optimization: CV.
My research focuses on how bureaucracies shape inequality, especially in labor markets.
I employ historical data & causal inference, with a hint of ML & NLP.
Research Interests: Labor & Orgnizational Economics; Causal Inference
Contact Information:
Email: alessio.giorgetta@unibocconi.it
Phone: + (39) 370 708 5826
Bocconi University, Via Roentgen 1, 20136 Milano, Office 3C3-03
Born and raised in the Italian mountains around the Lake of Como, I became interested in Economics during high-school. I hold a M.Sc. in Economics and Econometrics with Academic Honors from University of Bologna, where my interests narrowed to labor economics and causal inference. Under the supervision of Professor Enrico Cantoni I ran a nationwide RCT to evaluate the discrimination school bureaucrats enact against foreigners. To do so, I employed new techniques in the realm of Natural Language Programming & Machine Learning. You can find my dissertation draft, slides and codes here!
During my M.Sc. I worked as a research assistant for Professors Nicola Mastrorocco (Bologna) and Edoardo Teso (Bocconi - Northwestern). I used Python to cluster-compute optimal paths in time-varying networks and Stata to handle large (+20GB) spatio-temporal datasets. Meanwhile, I was a teaching assistant of undergraduate macroeconomics, holding exercise sessions and correcting exams. Finally, I was selected to participate as a member of the Bologna's team in the 2025 Econometric Game.
Currently, I started a new adventure as a Pre-Doctoral Fellow at LEAP - Bocconi under the guidance of Professor Erika Deserranno! I mainly use Stata & Python to perform econometric analysis in Labor and Organizational research.
My research focuses on how bureaucratic procedures shape discrimination, growth and labor outcomes. To do so I employ historical data and new econometrics techniques for causal identification.
When not browsing the IPUMS Website, you can find me trekking or climbing :)